Reply: metrics to assess machine learning models

Author:

Rajkomar AlvinORCID,Dai Andrew M.,Sun Mimi,Hardt Michaela,Chen Kai,Rough Kathryn,Dean Jeffrey

Publisher

Springer Science and Business Media LLC

Subject

Health Information Management,Health Informatics,Computer Science Applications,Medicine (miscellaneous)

Reference5 articles.

1. Romero-Brufau, S., Huddleston, J. M., Escobar, G. J. & Liebow, M. Why the C-statistic is not informative to evaluate early warning scores and what metrics to use. Crit. Care. 19, 285 (2015).

2. Rajkomar, A. & Oren, E. Deep Learning for Electronic Health Records. Google AI Blog http://ai.googleblog.com/2018/05/deep-learning-for-electronic-health.html .

3. Che, Z., Purushotham, S., Cho, K., Sontag, D. & Liu, Y. Recurrent neural networks for multivariate time series with missing values. Sci. Rep. 8, 6085 (2018).

4. Walsh, C. & Hripcsak, G. The effects of data sources, cohort selection, and outcome definition on a predictive model of risk of thirty-day hospital readmissions. J. Biomed. Inform. 52, 418–426 (2014).

5. Boyd, K., Eng, K. H. & Page, C. D. In: H., Blockeel, K., Kersting, S., Nijssen, & F. Železný (Eds). Machine Learning and Knowledge Discovery in Databases 451–466 (Springer Berlin Heidelberg, 2013).

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